> ------------- > from scipy import linalg > facearray-=facearray.mean(0) #mean centering > u, s, vt = linalg.svd(facearray, 0) > scores = u*s > facespace = vt.T > # reconstruction: facearray ~= dot(scores, facespace.T) > explained_variance = 100*s.cumsum()/s.sum()
hi i am a newbie in this area of eigenface based methods..is this how to reconstruct face images from eigenfaces? facearray ~= dot(scores, facespace.T) i guess it translates to facearray = dot(sortedeigenvectorsmatrix , facespace) i tried it and it produces (from facearray) a set of images very similar(but dark and bit smudged around eyes,nose..) to the original set of face images.. oharry _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
